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We developed and tested a complete measurement system to quantify CO2 and CH4 emissions at the scale of an industrial site based on the innovative sensor Airborne Ultra-light Spectrometer for Environmental Application (AUSEA), operated on board uncrewed aircraft vehicles (UAVs). The AUSEA sensor is a new light-weight (1.4 kg) open-path laser absorption spectrometer simultaneously recording in situ CO2 and CH4 concentrations at high frequency (24 Hz in this study) with precisions of 10 ppb for CH4 and 1 ppm for CO2 (when averaged at 1 Hz). It is suitable for industrial operation at a short distance from the sources (sensitivity up to 1000 ppm for CO2 and 200 ppm for CH4). Greenhouse gas concentrations monitored by this sensor throughout a plume cross section downwind of a source drive a simple mass balance model to quantify emissions from this source. This study presents applications of this method to different pragmatic cases representative of real-world conditions for oil and gas facilities. Two offshore oil and gas platforms were monitored for which our emissions estimates were coherent with mass balance and combustion calculations from the platforms. Our method has also been compared to various measurement systems (gas lidar, multispectral camera, infrared camera including concentrations and emissions quantification system, acoustic sensors, ground mobile and fixed cavity ring-down spectrometers) during controlled-release experiments conducted on the TotalEnergies Anomaly Detection Initiatives (TADI) test platform at Lacq, France. It proved suitable to detect leaks with emission fluxes down to 0.01 gs-1 , with 24 % of estimated CH4 fluxes within the - 20 % to + 20 % error range, 80 % of quantifications within the - 50 % to + 100 % error range and all of our results within the - 69 % to + 150 % error range. Such precision levels are better ranked than current top-down alternative techniques to quantify CH4 at comparable spatial scales. This method has the potential to be operationally deployed on numerous sites and on a regular basis to evaluate the space- and time-dependent greenhouse gas emissions of oil and gas facilities. [ABSTRACT FROM AUTHOR]

Fugitive methane (CH 4) emissions occur in the whole chain of oil and gas production, including from extraction, transportation, storage, and distribution. Such emissions are usually detected and quantified by conducting surveys as close as possible to the source location. However, these surveys are labour-intensive, are costly, and fail to not provide continuous emissions monitoring. The deployment of permanent sensor networks in the vicinity of industrial CH 4 emitting facilities would overcome the limitations of surveys by providing accurate emission estimates, thanks to continuous sampling of emission plumes. Yet high-precision instruments are too costly to deploy in such networks. Low-cost sensors using a metal oxide semiconductor (MOS) are presented as a cheap alternative for such deployments due to their compact dimensions and to their sensitivity to CH 4. In this study, we demonstrate the ability of two types of MOS sensors (TGS 2611-C00 and TGS 2611-E00) manufactured by Figaro® to reconstruct a CH 4 signal, as measured by a high-precision reference gas analyser, during a 7 d controlled release campaign conducted by TotalEnergies® in autumn 2019 near Pau, France. We propose a baseline voltage correction linked to atmospheric CH 4 background variations per instrument based on an iterative comparison of neighbouring observations, i.e. data points. Two CH 4 mole fraction reconstruction models were compared: multilayer perceptron (MLP) and second-degree polynomial. Emission estimates were then computed using an inversion approach based on the adjoint of a Gaussian dispersion model. Despite obtaining emission estimates comparable with those obtained using high-precision instruments (average emission rate error of 25 % and average location error of 9.5 m), the application of these emission estimates is limited to adequate environmental conditions. Emission estimates are also influenced by model errors in the inversion process. [ABSTRACT FROM AUTHOR]

Fugitive methane (CH4) emission occur in the whole chain of oil and gas production, from the extraction, transportation, storage and distribution. The detection and quantification of such emissions are conducted usually from surveys as close as possible to the source location. However, these surveys are labor intensive, costly and they do not provide continuous monitoring of the emissions. The deployment of permanent networks of sensors in the vicinity of industrial facilities would overcome the limitations of surveys by providing accurate estimates thanks to continuous sampling of the plumes. High precision instruments are too costly to deploy in such networks. Low-cost sensors like Metal oxide semiconductors (MOS) are presented as a cheap alternative for such deployments due to its compact dimensions and to its sensitivity to CH4. In this study we test the ability of two types of MOS sensors from the manufacturer Figaro® (TGS 2611-C00 and TGS 2611-E00) deployed in six chambers to reconstruct an actual signal from a source in open air corresponding to a series of controlled CH4 releases and we assess the accuracy of the emission estimates computed from reconstructed CH4 mole fractions from voltages measurements of these sensors. A baseline correction of the voltage linked to background variations is presented based on an iterative comparison of neighboring observations. Two reconstruction models were compared, multilayer perceptron (MLP) and 2nd degree polynomial, providing similar performances meeting our target requirement on all the chambers when the input variable is the TGS 2611-C00 sensor. The emission estimates were then computed using an inversion approach based on the adjoint of a Gaussian dispersion model obtaining promising results with an emission rate error of 25% and a location error of 9.5 m. [ABSTRACT FROM AUTHOR]

We developed an innovative tool to quantify CO2 and CH4 emissions at the scale of an industrial site, based on a mass balance approach relying on a newly developed light-weight (1.4 kg) open path laser absorption spectrometer operable on-board Unmanned Aircraft Vehicles (UAVs). This spectrometer simultaneously records in situ CO2 and CH4 concentrations at high frequency (24 Hz in this study) with precisions of 10 ppb for CH4 and 1 ppm for CO2 averaged at 1 Hz. The large range of measurable concentrations, up to 1000 ppm for CO2 and 200 ppm for CH4, makes this analyzer suitable for operation on industrial sites at a short distance from the emission sources, therefore avoiding many logistical and legal limits associated with most long-range airborne observations. To quantify the emissions, high spatial resolution atmospheric concentration measurements obtained throughout a plume cross-section downwind of a source within the limited UAV flight period are exploited by calculations using a mass balance approach. This high spatial resolution, allowed by the high acquisition frequency, limits the use of horizontal interpolation, thus gaining in precision compared to current airborne alternative quantification techniques. A field validation campaign, conducted on the TotalEnergies TADI test platform at Lacq, France, consisted in controlled CO2 and CH4 leak experiments to which several institutes participated with various measurement systems (gas LiDAR, multispectral camera, infrared camera including concentrations and emissions quantification system, acoustic sensors, ground mobile and fixed Cavity RingDown Spectrometers). Our method was proved suitable to detect leaks during controlled release experiments with emission fluxes down to 0.01 g s-1, with 24 % of estimated CH4 fluxes within the -20 % to +20 % error range, 80 % of quantifications within the 50 % to +100 % error range and all of our results within the -69 % to +150 % error range. Such precision levels are better ranked than current top-down alternative techniques to quantify CH4 at comparable spatial scales. Observations across the plume of two offshore oil and gas platforms operated by TotalEnergies in the North Sea were used to quantify the instantaneous greenhouse gases emissions of these facilities and are coherent with reference emissions for these platforms estimated by mass balance and combustion calculations for CO2. The operational deployment of such instruments and quantification methods, on a large scale and on a regular basis, potentially with fully autonomous UAVs, will allow the quantification of the time dependent greenhouse gases emissions of numerous oil and gas facilities. [ABSTRACT FROM AUTHOR]

We present a local-scale atmospheric inversion framework to estimate the location and rate of methane (CH4) and carbon dioxide (CO2) releases from point sources. It relies on mobile near-ground atmospheric CH4 and CO2 mole fraction measurements across the corresponding atmospheric plumes downwind the sources, on high-frequency meteorological measurements, and a Gaussian plume dispersion model. It exploits the spread of the positions of individual plume cross-sections and the integrals of the gas mole fractions above the background within these plume cross-sections to infer the position and rate of the releases. It has been developed and applied to provide estimates of brief controlled CH4 and CO2 point source releases during a one-week campaign in October 2018 at the TOTAL's experimental platform TADI in Lacq, France. These releases lasted typically 4 to 8 minutes and covered a wide range of rates (0.3 to 200 gCH4/s and 0.2 to 150 gCO2/s) to test the capability of atmospheric monitoring systems to react fast to emergency situations in industrial facilities. It also allowed testing their capability to provide precise emission estimates for the application of climate change mitigation strategies. However, the low and highly varying wind conditions during the releases added difficulties to the challenge of characterizing the atmospheric transport over the very short duration of the releases. We present our series of measurements of CH4 and CO2 mole fractions using instruments onboard a car that drives along the roads ~50 to 150 m downwind the 40 m x 60 m area of controlled releases for each of the releases and the results from the inversions of the release locations and rates. The comparisons of these results to the actual position and rate of the controlled release indicate a 20 %-30 % average error on the release rates and a ~30-40 m errors in the estimates of the release locations. These results are shown to be promising especially since better results could be expected for longer releases and under meteorological conditions more favorable to local scale dispersion modeling. [ABSTRACT FROM AUTHOR]

For many plants, the annual average impact is significantly lower than the regulation limit. Nevertheless, in some critical meteorological conditions, pollution peaks may occur. The present study describes an original control method for refinery emissions based on meteorological forecast and dispersion modelling, to avoid SO2 pollution peaks. An integrated operational tool has been developed to forecast, automatically, 24 h a day, the environmental SO2 impact around the plant for the next two days. The operational system allows the site to avoid the major part of pollution peaks and the associated cost. [ABSTRACT FROM AUTHOR]